Building an AI team is not an easy task. Sometimes it is easier to use the services of an external team when creating a solution.
But consulting firms have their drawbacks:
• doing things more complicated than they should be;
• can not always meet the deadlines, according to the budget;
• Can’t fully deliver on the promise of a working machine learning solution.
Separating a leading consulting firm from newcomers is not easy if you’re just starting out with machine learning. With the help of the guide, you can find a consultation worthy of cooperation.
We’ll provide a few things to look out for, what questions to ask yourself before hiring a firm. We will give you valuable advice to avoid common mistakes that lead to failure or exceeding the planned budget.
Things to Look Out for When Consulting Machine Learning
1. Make machine learning easier.
A machine learning consultant should know how to explain how it works in a language you can understand.
What is Machine Learning? If you are using AI at the moment, then almost always it is about creating a system capable of receiving data and making predictions.
In order to be able to make predictions, machine learning algorithms reveal hidden patterns associated with correct predictions when looking at a large number of training examples.
To get a visual illustration of model learning, you need to find patterns and then make predictions, check out a visual introduction to machine learning.
2. Get to their feet quickly.
An artificial intelligence consulting firm can answer if the idea is promising almost immediately.
In most cases, experienced specialists will be able to tell in a few minutes a decision whether it makes sense to continue further in a few minutes after the essence of the problem and the available data are presented.
They will not provide a guarantee that there will be a significant result, but they will tell you what ideas can be implemented. You need to create a proof of concept to prove what you want to predict.
3. Able to say “No”.
Will the consulting company be able to work on machine learning according to your idea, or will they suggest the best option, even if it is not what you expected?
Some machine learning ideas are bad when you look at them closely. If the necessary data is missing or if you do not see a clear solution, they should say so.
Not every project needs AI.
Clients regularly contact to get advice on machine learning, when simple schemes can give about 90% of the results. Recommended not to use machine learning, point in the right direction.
Not every project is possible to implement, and there are even fewer worthy attention.
Look for a machine learning agency that can tell you which ideas to ditch right away and which ones to focus on to get results.
4. Share their experiences openly.
Don’t let the company hide behind a nonproliferation agreement. A reputable company should indicate some projects and voice real numbers and names. We must tell who we worked with before, what problems we solved and what came of it.
Cooperate with a reliable agency that has reliable recommendations and will announce which projects have been implemented, what they have done for this and what they have achieved. Ask if projects are research or POC, or are used by clients on a regular basis.
5. Asking the right questions.
After the meeting, did you feel like they were asking the right questions? Were they clarifying, trying to find out the essence of the problem?
To implement the project, you need the company to learn as much as possible about your business. They should be able to repeat the goals in a way that pleases the client.
In the process of machine learning, specialists will make serious decisions that will be decisive as a result of the customer’s project. They can give ideas, make suggestions on how to improve. They can do it efficiently only when they correctly understand the essence of your business and tasks. If you need professional machine learning consulting services – Data-Science UA will help you.
